Show the code
# Learn more about Code Cells: https://quarto.org/docs/reference/cells/cells-jupyter.html
# Include and execute your code here
from palmerpenguins import load_penguins
df = load_penguins()# Learn more about Code Cells: https://quarto.org/docs/reference/cells/cells-jupyter.html
# Include and execute your code here
from palmerpenguins import load_penguins
df = load_penguins()Include the tables created from PY4DS: CH2 Data Visualization used to create the above chart (Hint: copy the code from 2.2.1. The penguins data frame and paste each in the cells below)
# Include and execute your code here
import pandas as pd
import numpy as np
from lets_plot import *
from palmerpenguins import load_penguins
# Load the Palmer Penguins dataset
penguins = load_penguins()
# Display the first few rows of the dataset for inspection
print("Preview of Palmer Penguins dataset:")
print(penguins.head())
# Setup LetsPlot for HTML rendering
LetsPlot.setup_html(isolated_frame=True) Preview of Palmer Penguins dataset:
species island bill_length_mm bill_depth_mm flipper_length_mm \
0 Adelie Torgersen 39.1 18.7 181.0
1 Adelie Torgersen 39.5 17.4 186.0
2 Adelie Torgersen 40.3 18.0 195.0
3 Adelie Torgersen NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0
body_mass_g sex year
0 3750.0 male 2007
1 3800.0 female 2007
2 3250.0 female 2007
3 NaN NaN 2007
4 3450.0 female 2007
import pandas as pd
import numpy as np
from lets_plot import *
from palmerpenguins import load_penguins
# Load the Palmer Penguins dataset
penguins = load_penguins()
# Display the first few rows of the dataset for inspection
print(penguins['species']) # Corrected line
# Setup LetsPlot for HTML rendering
LetsPlot.setup_html(isolated_frame=True)0 Adelie
1 Adelie
2 Adelie
3 Adelie
4 Adelie
...
339 Chinstrap
340 Chinstrap
341 Chinstrap
342 Chinstrap
343 Chinstrap
Name: species, Length: 344, dtype: object
Recreate the example charts from PY4DS: CH2 Data Visualization of the textbook. (Hint: copy the chart code from 2.2.3. Creating a Plot, one for each cell below)
# Include and execute your code here
import pandas as pd
import numpy as np
from lets_plot import *
from palmerpenguins import load_penguins
penguins = load_penguins()
penguinspecies = penguins['species']
# Create a basic plot
(
ggplot(data=penguins, mapping=aes(x="bill_depth_mm", y="body_mass_g"))
+ geom_point(aes(color="species", shape="species"))
+ geom_smooth(method="lm")
+ labs(
title="Body mass and Bill depth",
subtitle="Dimensions for Adelie, Chinstrap, and Gentoo Penguins",
x="Bill depth (mm)",
y="Body mass (g)",
color="Species",
shape="Species",
)
)This code reates a scatter plot to visualize the relationship between Bill depth and body mass of penguins using the Palmer Penguins dataset. ↑
# Include and execute your code here
import pandas as pd
import numpy as np
from lets_plot import *
from palmerpenguins import load_penguins
penguins = load_penguins()
penguinspecies = penguins['species']
(
ggplot(data=penguins, mapping=aes(x="flipper_length_mm", y="body_mass_g"))
+ geom_point(aes(color="species", shape="species"))
+ geom_smooth(method="lm")
+ labs(
title="Body mass and flipper length",
subtitle="Dimensions for Adelie, Chinstrap, and Gentoo Penguins",
x="Flipper length (mm)",
y="Body mass (g)",
color="Species",
shape="Species",
)
)This code reates a scatter plot to visualize the relationship between flipper length and body mass of penguins using the Palmer Penguins dataset. ↑